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The fuzzy PID control optimized by genetic algorithm for trajectory tracking of robot arm

机译:机器人轨迹轨迹跟踪遗传算法优化的模糊PID控制

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According to the characteristics of strong coupling and nonlinearity of the robot arm control system, a fuzzy PID controller optimized by the genetic algorithm (GA) is proposed. The method realizes the control of nonlinear system and improves the dynamic response speed and adaptive capacity of the system by the fuzzy control strategy. Taking the overall performance index as the fitness function, the genetic algorithm is used to optimize and self-tune the PID control parameters to meet the design requirements of system which can make up the shortage of low precision of fuzzy control. In the control of robot arm, the fuzzy PID control based on parameter optimization by the genetic algorithm has the characteristics of fast response and small overshoot. In the presence of external disturbances and parameter variation of the object, system has a certain ability to adapt. Simulation results show that the algorithm is effective and practical, and can be used in other control objects and processes.
机译:根据机器人臂控制系统的强耦合和非线性的特性,提出了一种由遗传算法(GA)优化的模糊PID控制器。该方法实现了非线性系统的控制,通过模糊控制策略提高了系统的动态响应速度和自适应容量。将整体性能指数作为健身功能,遗传算法用于优化和自调谐PID控制参数,以满足系统的设计要求,可以弥补模糊控制低精度的缺点。在控制机器人臂的控制中,基于遗传算法的参数优化的模糊PID控制具有快速响应和小过冲的特点。在存在外部干扰和对象的参数变化的情况下,系统具有一定的适应能力。仿真结果表明,该算法是有效实用的,可用于其他控制对象和过程。

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